We present a new technique for the compression of remote-sensing hyperspectral images based on wavelet transform and zerotree coding of coefficients. In order to improve encoding efficiency, the image is first segmented in a small number of regions with homogeneous texture. Then, a shape-adaptive wavelet transform is carried out on each region, and the resulting coefficients are finally encoded by a shape-adaptive version of SPIHT. Thanks to the segmentation map (sent as a side information) region boundaries are faithfully preserved, and selective encoding strategies can be easily implemented. In addition, by-now homogeneous region textures can be more efficiently encoded. © 2004 IEEE.
Region-oriented compression of multispectral images by shape-adaptive wavelet transform and spiht
Cagnazzo M.;
2004
Abstract
We present a new technique for the compression of remote-sensing hyperspectral images based on wavelet transform and zerotree coding of coefficients. In order to improve encoding efficiency, the image is first segmented in a small number of regions with homogeneous texture. Then, a shape-adaptive wavelet transform is carried out on each region, and the resulting coefficients are finally encoded by a shape-adaptive version of SPIHT. Thanks to the segmentation map (sent as a side information) region boundaries are faithfully preserved, and selective encoding strategies can be easily implemented. In addition, by-now homogeneous region textures can be more efficiently encoded. © 2004 IEEE.
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